CN107732902A - Power distribution network economical operation monitoring and evaluation method - Google Patents
Power distribution network economical operation monitoring and evaluation method Download PDFInfo
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- CN107732902A CN107732902A CN201710947488.2A CN201710947488A CN107732902A CN 107732902 A CN107732902 A CN 107732902A CN 201710947488 A CN201710947488 A CN 201710947488A CN 107732902 A CN107732902 A CN 107732902A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Abstract
The present invention relates to a kind of convenient and swift, safely and effectively power distribution network economical operation monitoring and evaluation method.Comprise the following steps：Step 1, information channel is utilized（GPRS, CDMA etc.）, by power information acquisition system, gather specially public change side intelligent electric energy meter voltage U, current value I；Step 2, according to the collection current value I in step 1, three facial difference degree of unbalancedness F degree of unbalancedness Ps balanced with three-phase is calculated respectively；The present invention is reasonable in design and easy to use.This patent, mainly according to transformer technology parameter, with reference to actual load situation, determines the indexs such as efficiency, power loss, and then judge transformer economic operation situation from the basic theory of transformer station high-voltage side bus by the size of load factor.
Description
Technical field
The present invention relates to power distribution network economical operation monitoring and evaluation method.
Background technology
At present, as intelligent distribution network is information-based, automation, interactive horizontal raising and mutually oozes with Internet of Things
Thoroughly with merging, electric power enterprise measures system inner accumulation mass data, such as user power utilization data, management and running data, GIS numbers
According to the detection of, equipment and Monitoring Data and breakdown repair data etc..Outside measurement system, electric power enterprise also have accumulated a large amount of fortune
Seek data, such as Customer Service Information, business administration data and electricity market data.Except electric power enterprise internal data, go back
There are many potential external data sources, as the GPS of internet, mobile device, and community service department database can be carried
The big data of confession is available for excavating and utilized.By carrying out systematicness and strategy to the big data of the inside and outside acquisition of intelligent grid
Property management, the feedback element of more horn of plenty can be provided for operation of power networks, help to correct and strengthen Electric Power Network Planning and operation.
How the problem of effective monitoring turns into urgent need to resolve with evaluation is carried out to power distribution network.
The content of the invention
The technical problems to be solved by the invention are generally speaking to provide a kind of power distribution network economical operation monitoring and evaluation side
Method；The technical problem and acquirement beneficial effect solved in detail content in aftermentioned content and combination embodiment is specific
Description.
The present invention is applied to power distribution network and carries out effective monitoring and evaluation, can promote the operation of power distribution network Quality and economy, have
When helping reduce Distribution Network Equipment investment, raising distribution network reliability, reduction electricity stealing, shortening distribution network failure repairing
Between, improve photovoltaic plant economy etc., there is larger economic and social profit.
To solve the above problems, the technical solution used in the present invention is：
A kind of convenient and swift, safely and effectively power distribution network economical operation monitoring of the present invention and evaluation method.Including following
Step：
Step 1, using information channel (GPRS, CDMA etc.), by power information acquisition system, specially public change side intelligence is gathered
Electric energy meter voltage U, current value I；
Step 2, according to the collection current value I in step 1, it is balanced with three-phase not that three facial difference degree of unbalancedness F are calculated respectively
Degree of balance P；
Wherein,
In formula：Imax is three-phase maximum current, and Imin is three-phase minimum current, and three-phase circuit electric current is respectively IA、IB、IC,
Unit is A；
Step 3, the three facial difference degree of unbalancedness F degree of unbalancedness Ps balanced with three-phase obtained for step 2：When 24 point curves
It is middle to meet F in the presence of 8 points>80% and 3P>When 80%, then ammeter user judges high doubtful imbalance；When in 24 point curves exist 2
The point of point -7 meets F>80% and 3P>80%, then ammeter user be included in key monitoring storehouse (key monitoring storehouse i.e. power information gather
The ammeter user that system preferably monitors)；When being not present in 24 point curves or only 1 point meets F>80% and 3P>80%, then return
Step 1 resurveys calculating；
Step 4, the high doubtful uneven transparent main table split-phase load E of ammeter user in step 3 is recorded, calculates three-phase and bear
Lotus degree of unbalancedness Q；
In formula：Emax is three-phase peak load, and Emin is three-phase minimum current load, and three-phase circuit load is respectively EA、
EB、EC, unit kw；
Step 5, for the Q value in step 4；Work as Q>20%, then ammeter user be determined as three-phase imbalance user, Q<
20%, then ammeter user be included in step 3 key monitoring storehouse；
Step 6, first, copied according to three-phase imbalance user in step 5 (i.e. public to become user F170) centralized automatic meter-reading electric energy meter
Ammeter information；Then, according to copy reading ammeter information, calculate respectively per phase number of users in three-phase imbalance user, and per phase
Charge value (kW kilowatt hours), administered for three-phase imbalance；
Step 7, according to every phase number of users in step 6 and per phase charge value, count in power information acquisition system
The abnormal six characteristic amounts of power supply area, capacity of distribution transform, line loss per unit, load factor, three-phase current unbalance, power factor；Its
In,
Power supply area is divided into city, outskirts of a town, county town and the class of rural area 4 according to the affiliated power supply unit of taiwan area；
Capacity of distribution transform processing is discrete variable, is divided into 3 classes according to transformer capacity：It is small-sized when being positioned as less than 100kVA,
It is medium-sized when being defined as more than 100kVA and less than 315kVA；When
Line loss per unit processing is discrete variable, is divided into 3 classes：When less than 2% or higher than 100% to be abnormal；When more than 2% and small
It is normal in 10%；Damaged when more than 10% and less than 100% to be high；
Load factor processing is discrete variable, and transformer station high-voltage side bus operating mode is divided into 5 classes：When less than 6%；For zero load；When big
It is underloading in 6% and less than 20%；It is normal when more than 20% and less than 80%；When more than 80% and less than 100%, attaching most importance to
Carry；When more than 100%, for overload；
Step 8, by the three-phase current unbalance in step 7, power factor, the abnormal three class event frequencies of the super appearance of load
As continuous variable；And collectively form characteristic value square with the capacity of distribution transform in step 7, line loss per unit, load factor this 3 class discrete variable
Battle array；
As shown in table 1：
The eigenvalue matrix of table 1
Step 9, Two-step cluster is chosen as cluster algorithm (algorithm and hierarchical clustering method and K- means Methods
Compared to advantages below：First, it can also be discrete variable that the variable for cluster, which can be continuous variable,；Second, in occupancy
It is few to deposit resource, it is very fast for big data quantity, arithmetic speed；Third, clustered using statistic as range index, while again
Optimal classification number can even be determined come " automatically " suggestion according to certain SS, correctness as a result more has guarantor
Barrier.)；The software for choosing application is IBM SPSS Statistics 22.SPSS softwares；(SPSS is Statistical
Product and Service Solutions softwares are the leaders of the professional statistical analysis software in the whole world, are directed to helping always
The ability for helping enterprises and institutions to improve Scientific application statistical analysis technique.It contains abundant statistical analysis algorithms, Er Qie
Experienced using application of the client during whole statistical analysis is more considered in aspect, it is its succinct interface, perfect
Data preparatory function and outstanding chart fan-out capability cause SPSS softwares in the global organization user for having more than 250,000, and into
For the main flow statistical analysis software of the country.)
Step 10, analysis is calculated：The characteristic value sample in step 8 is imported into SPSS first, generates data cluster；
Two-step cluster is chosen again, and the taiwan area load factor in step 8, taiwan area userbase, transformer capacity are set to and " divided
Class variable ", the three-phase imbalance in step 8, the super appearance of load, power factor exception, overcurrent are set to " continuous variable "；It is poly-
Class criterion chooses " Schwartz bayesian criterion "；Number of clusters chooses " automatically determining "；
Finally start cluster analysis.
Power distribution network efficiency of economic operations directly influences the cost and benefit of power system.The loss of distribution transforming accounts for circuit damage
The 30% of consumption, and ratio during distribution transforming underloading shared by transformer loss is bigger, realizes that the economical operation of distribution transforming is to ensure that power network section
The important means of damage can drop.
Transformer station high-voltage side bus analysis method, the typically basic theory from transformer station high-voltage side bus, mainly according to transformer technology
Parameter, with reference to actual load situation, the indexs such as efficiency, power loss are determined by the size of load factor, and then judge to become
Depressor Economic Status.
In order to more intuitively reflect distribution transforming operation conditions, power information acquisition system data information is relied on, while will cluster
Algorithm is applied in distribution transforming economical operation signature analysis, extracts distribute-electricity transformer district base profile and multiplexing electric abnormality information as feature
Value, distribution transforming operation characteristic is analyzed, proposes feasible suggestion.According to the big I of load factor in distribution transforming running by distribution transforming running status
It is divided into four kinds of running statuses such as underloading, normal, heavy duty, overload.The present invention has advantages below：
1. can accurate judgement tri-phase unbalance factor, and for administer technological means is provided.
2. pair distribution transforming overall operation economic conditions carry out quantitatively evaluating.
3. relying on power information acquisition system, data are true and reliable.
4. there is stronger generalization.
Beneficial effects of the present invention not limited to this describes, and in order to preferably readily appreciate, enters in specific embodiment part
More detailed description is gone.
Brief description of the drawings
Fig. 1 is the logical schematic of the present invention.
Fig. 2 is the distribution transforming operation characteristic analysis method flow chart of the present invention.
Fig. 3 is the sample classification overview table figure of the present invention.
Fig. 4 is the metering anomalous event Clustering table figure of the present invention.
Fig. 5 is the taiwan area userbase Clustering table figure of the present invention.
Fig. 6 is the transformer capacity Clustering table figure of the present invention.
Fig. 7 is the loading condition Clustering table figure of the present invention.
Embodiment
Such as Fig. 1-7, a kind of convenient and swift, safely and effectively power distribution network economical operation monitoring of the invention and evaluation method.
Comprise the following steps：
Step 1, using information channel (GPRS, CDMA etc.), by power information acquisition system, specially public change side intelligence is gathered
Electric energy meter voltage U, current value I；
Step 2, according to the collection current value I in step 1, it is balanced with three-phase not that three facial difference degree of unbalancedness F are calculated respectively
Degree of balance P；
Wherein,
In formula：Imax is three-phase maximum current, and Imin is three-phase minimum current, and three-phase circuit electric current is respectively IA、IB、IC,
Unit is A；
Step 3, the three facial difference degree of unbalancedness F degree of unbalancedness Ps balanced with three-phase obtained for step 2：When 24 point curves
It is middle to meet F in the presence of 8 points>80% and 3P>When 80%, then ammeter user judges high doubtful imbalance；When in 24 point curves exist 2
The point of point -7 meets F>80% and 3P>80%, then ammeter user be included in key monitoring storehouse (key monitoring storehouse i.e. power information gather
The ammeter user that system preferably monitors)；When being not present in 24 point curves or only 1 point meets F>80% and 3P>80%, then return
Step 1 resurveys calculating；
Step 4, the high doubtful uneven transparent main table split-phase load E of ammeter user in step 3 is recorded, calculates three-phase and bear
Lotus degree of unbalancedness Q；
In formula：Emax is three-phase peak load, and Emin is three-phase minimum current load, and three-phase circuit load is respectively EA、
EB、EC, unit kw；
Step 5, for the Q value in step 4；Work as Q>20%, then ammeter user be determined as three-phase imbalance user, Q<
20%, then ammeter user be included in step 3 key monitoring storehouse；
Step 6, first, copied according to three-phase imbalance user in step 5 (i.e. public to become user F170) centralized automatic meter-reading electric energy meter
Ammeter information；Then, according to copy reading ammeter information, calculate respectively per phase number of users in three-phase imbalance user, and per phase
Charge value (kW kilowatt hours), administered for three-phase imbalance；
Step 7, according to every phase number of users in step 6 and per phase charge value, count in power information acquisition system
The abnormal six characteristic amounts of power supply area, capacity of distribution transform, line loss per unit, load factor, three-phase current unbalance, power factor；Its
In,
Power supply area is divided into city, outskirts of a town, county town and the class of rural area 4 according to the affiliated power supply unit of taiwan area；
Capacity of distribution transform processing is discrete variable, is divided into 3 classes according to transformer capacity：It is small-sized when being positioned as less than 100kVA,
It is medium-sized when being defined as more than 100kVA and less than 315kVA；When
Line loss per unit processing is discrete variable, is divided into 3 classes：When less than 2% or higher than 100% to be abnormal；When more than 2% and small
It is normal in 10%；Damaged when more than 10% and less than 100% to be high；
Load factor processing is discrete variable, and transformer station high-voltage side bus operating mode is divided into 5 classes：When less than 6%；For zero load；When big
It is underloading in 6% and less than 20%；It is normal when more than 20% and less than 80%；When more than 80% and less than 100%, attaching most importance to
Carry；When more than 100%, for overload；
Step 8, by the three-phase current unbalance in step 7, power factor, the abnormal three class event frequencies of the super appearance of load
As continuous variable；And collectively form characteristic value square with the capacity of distribution transform in step 7, line loss per unit, load factor this 3 class discrete variable
Battle array；
As shown in table 1：
The eigenvalue matrix of table 1
Step 9, Two-step cluster is chosen as cluster algorithm (algorithm and hierarchical clustering method and K- means Methods
Compared to advantages below：First, it can also be discrete variable that the variable for cluster, which can be continuous variable,；Second, in occupancy
It is few to deposit resource, it is very fast for big data quantity, arithmetic speed；Third, clustered using statistic as range index, while again
Optimal classification number can even be determined come " automatically " suggestion according to certain SS, correctness as a result more has guarantor
Barrier.)；The software for choosing application is IBM SPSS Statistics 22.SPSS softwares；(SPSS is Statistical
Product and Service Solutions softwares are the leaders of the professional statistical analysis software in the whole world, are directed to helping always
The ability for helping enterprises and institutions to improve Scientific application statistical analysis technique.It contains abundant statistical analysis algorithms, Er Qie
Experienced using application of the client during whole statistical analysis is more considered in aspect, it is its succinct interface, perfect
Data preparatory function and outstanding chart fan-out capability cause SPSS softwares in the global organization user for having more than 250,000, and into
For the main flow statistical analysis software of the country.)
Step 10, analysis is calculated：The characteristic value sample in step 8 is imported into SPSS first, generates data cluster；
Two-step cluster is chosen again, and taiwan area load factor, line loss per unit, the transformer capacity in step 8 are set to " classification change
Amount ", the three-phase imbalance in step 8, the super appearance of load, power factor are set to " continuous variable " extremely；Clustering criteria is chosen and " applied
Watt hereby bayesian criterion "；Number of clusters chooses " automatically determining "；
Finally start cluster analysis.
In addition,
In formula：E is evaluated equipment overall operation situation to run unhealthy degree.PiFor each event weights, according to warp
Test and cluster analysis result is drawn, the F health degrees of association, determined by the classification of classified variable and the frequency of continuous variable.
As intelligent meter all standing, full collecting work move forward steadily, acquisition system access critical point, specially public become and low pressure is used
The family of family metering device 2099.01 ten thousand, it is average daily to gather success rate 98.5% ,/day of gathered data amount 4.1 hundred million, day data increment
70G.Mass data resource is that acquisition system strengthened research is had laid a good foundation.The present invention is reasonable in design, cost is cheap, knot
Reality is durable, safe and reliable, simple to operate, time saving and energy saving, saves fund, be compact-sized and easy to use.
The present invention, which fully describes, to be disclosed in order to more clear, and is just no longer illustrated one by one for prior art.
Finally it should be noted that：The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
The present invention is described in detail with reference to the foregoing embodiments, it will be understood by those within the art that：It still may be used
To be modified to the technical scheme described in previous embodiment, or equivalent substitution is carried out to which part technical characteristic；Make
It is obvious that multiple technical schemes of the present invention, which are combined, for those skilled in the art.And these are changed or replaced
Change, the essence of appropriate technical solution is departed from the spirit and scope of technical scheme of the embodiment of the present invention.
Claims (5)
1. a kind of power distribution network economical operation monitoring and evaluation method, it is characterised in that：Comprise the following steps：Step 1, information is utilized
Passage, by power information acquisition system, gather specially public change side intelligent electric energy meter voltage U, current value I；Step 2, according to step 1
In collection current value I, calculate three facial difference degree of unbalancedness F degree of unbalancedness Ps balanced with three-phase respectively；Wherein,
（1）；（2）；In formula：Imax is three-phase maximum current, and Imin is three-phase minimum current, and three-phase circuit is electric
Stream is respectively IA、IB、IC,Unit is A；Step 3, the three facial difference degree of unbalancedness F injustice balanced with three-phase obtained for step 2
Weighing apparatus degree P：When meeting F in the presence of 8 points in 24 point curves>80% and 3P>When 80%, then ammeter user judges high doubtful imbalance；When
Meet F in the presence of 2. -7 points in 24 point curves>80% and 3P>80%, then ammeter user be included in key monitoring storehouse；When 24 point curves
In be not present or only 1 point meets F>80% and 3P>80%, then return to step 1 resurvey calculating.
2. power distribution network economical operation monitoring according to claim 1 and evaluation method, it is characterised in that:
Step 4, the high doubtful uneven transparent main table split-phase load E of ammeter user in step 3 is recorded, calculates three-phase load not
Degree of balance Q；（3）
In formula：Emax is three-phase peak load, and Emin is three-phase minimum current load, and three-phase circuit load is respectively EA、EB、EC,
Unit is kw；
Step 5, for the Q value in step 4；Work as Q>20%, then ammeter user be determined as three-phase imbalance user, Q<20%,
Then ammeter user is included in step 3 key monitoring storehouse.
3. power distribution network economical operation monitoring according to claim 2 and evaluation method, it is characterised in that:Step 6, first,
According to three-phase imbalance user centralized automatic meter-reading electric energy meter copy reading ammeter information in step 5；Then, according to copy reading ammeter information, divide
Ji Suan not be in three-phase imbalance user per phase number of users, and per phase charge value；
Step 7, according to every phase number of users in step 6 and per phase charge value, the power supply in power information acquisition system is counted
Region, capacity of distribution transform, line loss per unit, load factor, three-phase current unbalance, the abnormal six characteristic amounts of power factor；Wherein,
Power supply area is divided into city, outskirts of a town, county town and the class of rural area 4 according to the affiliated power supply unit of taiwan area；
Capacity of distribution transform processing is discrete variable, is divided into 3 classes according to transformer capacity：It is small-sized when being positioned as less than 100kVA, when big
It is defined as in 100kVA and less than 315kVA medium-sized；It is large-scale when being defined as more than 315kVA；
Line loss per unit processing is discrete variable, is divided into 3 classes：When less than 2% or higher than 100% to be abnormal；When being more than 2% and less than 10%
Normally；Damaged when more than 10% and less than 100% to be high;
Load factor processing is discrete variable, and transformer station high-voltage side bus operating mode is divided into 5 classes：When less than 6%；For zero load；When more than 6% and
It is underloading less than 20%；It is normal when more than 20% and less than 80%；When more than 80% and less than 100%, for heavy duty;When more than
100%, for overload;
Step 8, using the three-phase current unbalance in step 7, power factor, load it is super hold abnormal three class event frequencies as
Continuous variable；And collectively form eigenvalue matrix with the capacity of distribution transform in step 7, line loss per unit, load factor this 3 class discrete variable.
4. power distribution network economical operation monitoring according to claim 3 and evaluation method, it is characterised in that:Step 9, two are chosen
Step clustering procedure is cluster algorithm；The software for choosing application is IBM SPSS Statistics 22.
5. power distribution network economical operation monitoring according to claim 4 and evaluation method, it is characterised in that:
Step 10, analysis is calculated：The characteristic value sample in step 8 is imported into SPSS first, generates data cluster；
Two-step cluster is chosen again, and the taiwan area load factor in step 8, taiwan area userbase, transformer capacity are set to " classification change
Amount ", the three-phase imbalance in step 8, the super appearance of load, power factor exception, overcurrent are set to " continuous variable "；Cluster is accurate
Then choose " Schwartz bayesian criterion "；Number of clusters chooses " automatically determining "；
Last cluster analysis.
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| CN109685096A (en) * | 2018-10-25 | 2019-04-26 | 广东电网有限责任公司 | A kind of distribution transformer classification method based on fuzzy clustering |
| CN110727725A (en) * | 2019-09-26 | 2020-01-24 | 广西电网有限责任公司电力科学研究院 | Data interface based on distribution network operating efficiency monitoring and analysis |
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| CN107732902B (en) | 2021-01-08 |
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